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<h1>12-MySQL基于成本的优化</h1>

<div><span><div style="font-size: 14px; margin: 0; padding: 0; width: 100%;"><h3 style="line-height: 160%; box-sizing: content-box; font-weight: 700; font-size: 27px; color: #333;">1 什么是成本</h3>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">MySQL中一条查询语句的执行成本是由两方面组成的：</p>
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<p style="line-height: 160%; box-sizing: content-box; color: #333; margin: 0;"><strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">I/O成本</strong><br/>
我们的表经常使用的MyISAM、InnoDB存储引擎都是将数据和索引都存储到磁盘上的，当我们想查询表中的记录时，需要先把数据或者索引加载到内存中然后再操作。这个从磁盘到内存这个加载的过程损耗的时间称之为I/O成本。</p>
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<p style="line-height: 160%; box-sizing: content-box; color: #333; margin: 0;"><strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">CPU成本</strong><br/>
读取以及检测记录是否满足对应的搜索条件、对结果集进行排序等这些操作损耗的时间称之为CPU成本。</p>
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<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">对于InnoDB存储引擎来说，<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">页是磁盘和内存之间交互的基本单位</strong>，MySQ规定<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">读取一个页面花费的成本默认是1.0</strong>，<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">读取以及检测一条记录是否符合搜索条件的成本默认是0.2</strong>。1.0、0.2这些数字称之为<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">成本常数</strong>。</p>
<h3 style="line-height: 160%; box-sizing: content-box; font-weight: 700; font-size: 27px; color: #333;">2 单表查询的成本</h3>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;"><strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">优化步骤：</strong></p>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">在一条单表查询语句真正执行之前，MySQL的查询优化器会找出执行该语句所有可能使用的方案，对比之后找出成本最低的方案，这个成本最低的方案就是所谓的执行计划，之后才会调用存储引擎提供的接口真正的执行查询，这个过程总结一下就是这样：</p>
<ul style="line-height: 160%; box-sizing: content-box; display: block; list-style-type: disc; padding-left: 30px; margin: 6px 0 10px; color: #333;">
<li style="line-height: 160%; box-sizing: content-box; position: relative;">根据搜索条件，找出所有可能使用的索引</li>
<li style="line-height: 160%; box-sizing: content-box; position: relative;">计算全表扫描的代价</li>
<li style="line-height: 160%; box-sizing: content-box; position: relative;">计算使用不同索引执行查询的代价</li>
<li style="line-height: 160%; box-sizing: content-box; position: relative;">对比各种执行方案的代价，选取成本最低的那个</li>
</ul>
<h4 style="line-height: 160%; box-sizing: content-box; font-size: 20px; color: #333;">计算全表扫描的代价</h4>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">对于InnoDB存储引擎来说，全表扫描的意思就是把聚簇索引中的记录都依次和给定的搜索条件做一下比较，把符合搜索条件的记录加入到结果集，所以需要将聚簇索引对应的页面加载到内存中，然后再检测记录是否符合搜索条件。由于查询成本=I/O成本+CPU成本，所以计算全表扫描的代价需要两个信息：</p>
<ul style="line-height: 160%; box-sizing: content-box; display: block; list-style-type: disc; padding-left: 30px; margin: 6px 0 10px; color: #333;">
<li style="line-height: 160%; box-sizing: content-box; position: relative;">聚簇索引占用的页面数</li>
<li style="line-height: 160%; box-sizing: content-box; position: relative;">该表中的记录数</li>
</ul>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">MySQL为每个表维护了一个<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">统计信息</strong>，可以通过<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">SHOW TABLE STATUS</strong>语句来查看<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">表的统计信息</strong>，如：SHOW TABLE STATUS LIKE 'single_table'；<br/>
<img src="12-MySQL基于成本的优化_files/Image.png" type="image/png" data-filename="Image.png"/></p>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">以上统计选项中，有2个很重要：</p>
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<p style="line-height: 160%; box-sizing: content-box; color: #333; margin: 0;"><strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">Rows</strong><br/>
本选项表示表中的记录条数。对于使用MyISAM存储引擎的表来说，该值是准确的，对于使用InnoDB存储引擎的表来说，该值是一个估计值。</p>
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<li style="line-height: 160%; box-sizing: content-box; position: relative;">
<p style="line-height: 160%; box-sizing: content-box; color: #333; margin: 0;"><strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">Data_length</strong><br/>
本选项表示表占用的存储空间字节数。使用MyISAM存储引擎的表来说，该值就是数据文件的大小，对于使用InnoDB存储引擎的表来说，该值就相当于聚簇索引占用的存储空间大小，也就是说可以这样计算该值的大小：<br/>
<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">Data_length = 聚簇索引的页面数量 x 每个页面的大小</strong><br/>
single_table使用默认16KB的页面大小，而上边查询结果显示Data_length的值是1589248，所以我们可以反向来推导出聚簇索引的页面数量：<br/>
聚簇索引的页面数量 = 1589248 ÷ 16 ÷ 1024 = 97</p>
</li>
</ul>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">我们现在已经得到了聚簇索引占用的页面数量以及该表记录数的估计值，所以就可以计算全表扫描成本了：</p>
<ul style="line-height: 160%; box-sizing: content-box; display: block; list-style-type: disc; padding-left: 30px; margin: 6px 0 10px; color: #333;">
<li style="line-height: 160%; box-sizing: content-box; position: relative;">I/O成本：聚簇索引占用的页面数 x 1.0 + 1.1；</li>
<li style="line-height: 160%; box-sizing: content-box; position: relative;">CPU成本：聚簇索引中的总记录条数（包含叶子节点和非叶子节点） x 0.2 + 1.0；</li>
</ul>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">其中，加号后面的1.1和1.0分别是MySQL计算成本时的微调值，不必关心。</p>
<h4 style="line-height: 160%; box-sizing: content-box; font-size: 20px; color: #333;">计算使用不同索引执行查询的代价</h4>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">对于使用二级索引 + 回表方式的查询，设计MySQL的大叔计算这种查询的成本依赖两个方面的数据：</p>
<ul style="line-height: 160%; box-sizing: content-box; display: block; list-style-type: disc; padding-left: 30px; margin: 6px 0 10px; color: #333;">
<li style="line-height: 160%; box-sizing: content-box; position: relative;">
<p style="line-height: 160%; box-sizing: content-box; color: #333; margin: 0;">范围区间数-m<br/>
不论某个范围区间的二级索引到底占用了多少页面，查询优化器粗暴的认为读取索引的一个范围区间的I/O成本和读取一个页面是相同的。如 condition &gt; 1，那么范围区间数为1；condition in （1，2，3），是3个单点区间，那么范围区间数为3。</p>
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<li style="line-height: 160%; box-sizing: content-box; position: relative;">
<p style="line-height: 160%; box-sizing: content-box; color: #333; margin: 0;">需要回表的记录条数-n</p>
</li>
</ul>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">那么使用二级索引 + 回表的成本为：</p>
<ul style="line-height: 160%; box-sizing: content-box; display: block; list-style-type: disc; padding-left: 30px; margin: 6px 0 10px; color: #333;">
<li style="line-height: 160%; box-sizing: content-box; position: relative;">I/O成本：<br/>
m（读取二级索引的成本） + n x 1.0（回表的成本）</li>
<li style="line-height: 160%; box-sizing: content-box; position: relative;">CPU成本：<br/>
n x 0.2（回表时读取二级索引需要回表记录数的成本）+ n x 0.2（读取并检测回表后聚簇索引记录的成本） + 0.01（微调值）<br/>
<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">需要注意的是：不管读取记录时需不需要检测是否满足搜索条件，其成本都算是0.2</strong>。</li>
</ul>
<h4 style="line-height: 160%; box-sizing: content-box; font-size: 20px; color: #333;">基于索引统计数据的成本计算</h4>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">有时候使用索引执行查询时会有许多单点区间，比如使用IN语句就很容易产生非常多的单点区间，比如下边这个查询（下边查询语句中的...表示还有很多参数）：</p>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">SELECT * FROM single_table WHERE key1 IN ('aa1', 'aa2', 'aa3', ... , 'zzz')；</p>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">由于这个索引不是唯一二级索引，所以不能确定一个单点区间对应的二级索引记录的条数，需要计算，首先获取索引对应的B+树的区间最左记录和区间最右记录，然后计算出两条记录之间的记录数<br/>
（记录条数少的时候可以做到精确计算，多的时候只能估算）。MySQL把这种<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">通过直接访问索引对应的B+树来计算某个范围区间对应的索引记录条数的方式称之为index dive</strong>。</p>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">有零星几个单点区间的话，使用index dive的方式去计算这些单点区间对应的记录数也不是什么问题，但是当IN中的参数特别多的时候，进行index dive操作的成本就很高了，甚至计算单点区间对应,的索引记录条数的成本比直接全表扫描的成本都大，所以MySQL提供了一个系统变量<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">eq_range_index_dive_limit</strong>：<br/>
<img src="12-MySQL基于成本的优化_files/Image [1].png" type="image/png" data-filename="Image.png"/></p>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">也就是说如果我们的IN语句中的参数个数小于200个的话，将使用index dive的方式计算各个单点区间对应的记录条数，如果大于或等于200个的话，可就不能使用index dive了，要使用<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">索引统计数据</strong>来进行估算。怎么个估算法？继续往下看。</p>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">像会为每个表维护一份统计数据一样，MySQL也会<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">为表中的每一个索引维护一份统计数据</strong>，查看某个表中索引的统计数据可以使用<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">SHOW INDEX FROM 表名</strong>的语法，比如我们查看一下single_table的各个索引的统计数据可以这么写：<br/>
<img src="12-MySQL基于成本的优化_files/Image [2].png" type="image/png" data-filename="Image.png"/></p>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">现在最在意的是<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">Cardinality属性</strong>，<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">Cardinality</strong>直译过来就是<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">基数</strong>的意思，表示索引列中不重复值的个数。比如对于一个一万行记录的表来说，某个索引列的Cardinality属性是10000，那意味着该列中没有重复的值，如果Cardinality属性是1的话，就意味着该列的值全部是重复的。不过需要注意的是，对于InnoDB存储引擎来说，使用SHOW INDEX语句展示出来的某个索引列的Cardinality属性是一个估计值，并不是精确的。</p>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">具体计算方式：</p>
<ul style="line-height: 160%; box-sizing: content-box; display: block; list-style-type: disc; padding-left: 30px; margin: 6px 0 10px; color: #333;">
<li style="line-height: 160%; box-sizing: content-box; position: relative;">使用 <strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">SHOW TABLE STATUS 展示出的Rows值</strong>，也就是一个表中有多少条记录；</li>
<li style="line-height: 160%; box-sizing: content-box; position: relative;">使用 <strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">SHOW INDEX 展示出的Cardinality属性</strong></li>
</ul>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">结合这两个值可以计算出平均一个值的重复次数：</p>
<ul style="line-height: 160%; box-sizing: content-box; display: block; list-style-type: disc; padding-left: 30px; margin: 6px 0 10px; color: #333;">
<li style="line-height: 160%; box-sizing: content-box; position: relative;">一个值的重复次数 ≈ Rows ÷ Cardinality</li>
</ul>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">所以使用索引统计数据估算出的记录条数就是：</p>
<ul style="line-height: 160%; box-sizing: content-box; display: block; list-style-type: disc; padding-left: 30px; margin: 6px 0 10px; color: #333;">
<li style="line-height: 160%; box-sizing: content-box; position: relative;">一个值的重复次数 x IN的参数个数</li>
</ul>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">使用统计数据来计算单点区间对应的索引记录条数可比index dive的方式简单多了，但是它的致命弱点就是：不精确！。使用统计数据算出来的查询成本与实际所需的成本可能相差非常大。</p>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">在MySQL 5.7.3以及之前的版本中，eq_range_index_dive_limit的默认值为10，之后的版本默认值为<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">200</strong>。所以如果大家采用的是5.7.3以及之前的版本的话，很容易采用索引统计数据而不是index dive的方式来计算查询成本。<strong style="line-height: 160%; box-sizing: content-box; font-weight: 700;">当你的查询中使用到了IN查询，但是却实际没有用到索引，就应该考虑一下是不是由于 eq_range_index_dive_limit 值太小导致的。</strong></p>
<h3 style="line-height: 160%; box-sizing: content-box; font-weight: 700; font-size: 27px; color: #333;">3 连接查询的成本</h3>
<h4 style="line-height: 160%; box-sizing: content-box; font-size: 20px; color: #333;">Condition filtering</h4>
<p style="line-height: 160%; box-sizing: content-box; margin: 10px 0; color: #333;">MySQL中连接查询采用的是嵌套循环连接算法，驱动表会被访问一次，被驱动表可能会被访问多次，所以对于两表连接查询来说，它的查询成本由下边两个部分构成：</p>
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